{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlalchemy\n",
    "import pandas as pd\n",
    "import datetime\n",
    "import random\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlalchemy import create_engine\n",
    "conn = create_engine(\"mysql+pymysql://root:123456@localhost:3306/work_sql_1?charset=utf8\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "current_day = \"2020-07-01\"\n",
    "last_day = \"2020-06-29\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>tel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>539</td>\n",
       "      <td>6f7602c534ce83d367b3c53a4f36c0b7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>540</td>\n",
       "      <td>d750c7b30e85efceb15f9838548fc085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>541</td>\n",
       "      <td>4fcd26ac2390e3f54d1a72b87ba4c77c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>542</td>\n",
       "      <td>7c134ea8df6ab6e78143eba0a3445e6e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>543</td>\n",
       "      <td>0c883e4a18c193c84e9c4785adb4d847</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id                               tel\n",
       "0          539  6f7602c534ce83d367b3c53a4f36c0b7\n",
       "1          540  d750c7b30e85efceb15f9838548fc085\n",
       "2          541  4fcd26ac2390e3f54d1a72b87ba4c77c\n",
       "3          542  7c134ea8df6ab6e78143eba0a3445e6e\n",
       "4          543  0c883e4a18c193c84e9c4785adb4d847"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql1 = \"select id as customer_id,tel from  customer where id not in (select customer_id from mission group by customer_id);\"\n",
    "\n",
    "df_customer = pd.read_sql(\n",
    "    sql1,conn\n",
    ")\n",
    "df_customer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id\n",
       "0   2\n",
       "1  30\n",
       "2  14\n",
       "3  23\n",
       "4  16"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql2 = \"select id from salesstaff;\"\n",
    "\n",
    "df_salesstaff = pd.read_sql(\n",
    "    sql2,conn\n",
    ")\n",
    "\n",
    "df_salesstaff.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2,\n",
       " 30,\n",
       " 14,\n",
       " 23,\n",
       " 16,\n",
       " 3,\n",
       " 25,\n",
       " 12,\n",
       " 28,\n",
       " 22,\n",
       " 29,\n",
       " 8,\n",
       " 19,\n",
       " 26,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 11,\n",
       " 6,\n",
       " 13,\n",
       " 15,\n",
       " 4,\n",
       " 18,\n",
       " 17,\n",
       " 20,\n",
       " 1,\n",
       " 5,\n",
       " 7,\n",
       " 10,\n",
       " 9]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salesstaff_ids = df_salesstaff[\"id\"].values.tolist()\n",
    "salesstaff_ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 a\n",
      "1 b\n",
      "2 c\n"
     ]
    }
   ],
   "source": [
    "l = [\"a\",\"b\",\"c\"]\n",
    "for i ,l in enumerate(l):\n",
    "    print(i,l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'salesstaff_id': 2,\n",
       "  'customer_id': 539,\n",
       "  'this_tel': '6f7602c534ce83d367b3c53a4f36c0b7'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 540,\n",
       "  'this_tel': 'd750c7b30e85efceb15f9838548fc085'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 541,\n",
       "  'this_tel': '4fcd26ac2390e3f54d1a72b87ba4c77c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 542,\n",
       "  'this_tel': '7c134ea8df6ab6e78143eba0a3445e6e'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 543,\n",
       "  'this_tel': '0c883e4a18c193c84e9c4785adb4d847'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 544,\n",
       "  'this_tel': '19de7741b9d2fb317b820984cd7b46dd'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 545,\n",
       "  'this_tel': 'ec9817ef0722f3c76138dbc83228dc4c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 546,\n",
       "  'this_tel': '3271d5953121d680d7dbd6dc636d3e5d'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 547,\n",
       "  'this_tel': '5ecdda7fe15c3714f848a4f3e877b335'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 548,\n",
       "  'this_tel': '51267820d9645e83602584a17b31de10'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 549,\n",
       "  'this_tel': '42ac663921f03535e93498584e213399'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 550,\n",
       "  'this_tel': '28434be616a48e3afd41fad989618c59'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 551,\n",
       "  'this_tel': 'bb291924c8ffd9ff2e44b1ed0f3f4ab3'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 552,\n",
       "  'this_tel': 'baf8047a1550beb98d4ec50f73dc68ef'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 553,\n",
       "  'this_tel': '684d2daf7e56a338a753a9f86406eab1'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 554,\n",
       "  'this_tel': 'a1b8ce7cb0a43f156e2eaed3bfe3a1de'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 555,\n",
       "  'this_tel': 'c74db03d9a6a4f8ba710ae90443ea5a7'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 556,\n",
       "  'this_tel': '234277677a301203b2369544d52c40a6'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 557,\n",
       "  'this_tel': 'dc50a84b1163f535cb5712627ad5074c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 558,\n",
       "  'this_tel': '1365f5ae48dbedeb7a3eb77c544ec744'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 559,\n",
       "  'this_tel': '5c31eb0fe13a69cde0ed215a62916f2a'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 560,\n",
       "  'this_tel': '49583e3c50188987c3d4c7fa9e976ce8'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 561,\n",
       "  'this_tel': 'b876d76916a8e59fcd3a3d93df1eb074'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 562,\n",
       "  'this_tel': '8c46781ac04196a16a12d1ab3558bafd'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 563,\n",
       "  'this_tel': '1207bb574951d508de0d767f41635326'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 564,\n",
       "  'this_tel': 'db606837d7882ce41033ae5cb4e3423a'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 565,\n",
       "  'this_tel': 'a06e1d9c5a8c1153a54e4afb9283989b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 566,\n",
       "  'this_tel': 'a9eee1b73729a160607c5207d1564910'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 567,\n",
       "  'this_tel': '0a107d4146b08e3c07cbe2732ba34412'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 568,\n",
       "  'this_tel': '8894a3672eaf305ad6b8a910f0097e6d'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 569,\n",
       "  'this_tel': 'a8364563482cbf0abf68e0723a6e9dba'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 570,\n",
       "  'this_tel': 'fac407cd3575f4e6582da2dbc8884d36'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 571,\n",
       "  'this_tel': '6ccef8d221228afc009630d87edc1d3c'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 572,\n",
       "  'this_tel': '8c80d48fa13933118eee61784a57e520'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 573,\n",
       "  'this_tel': '50059fc8ea6e4eddfe7fade624536a4b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 574,\n",
       "  'this_tel': '7e9c391cc6a253f16a58154db5c4fc54'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 575,\n",
       "  'this_tel': 'a8995d22e8f6d654593be1b128d8dba9'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 576,\n",
       "  'this_tel': '7de85a1fc2f6a0713ebf8f6b51d64ec1'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 577,\n",
       "  'this_tel': 'aa985d8a9150f995bfaddcad6b0cd9df'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 578,\n",
       "  'this_tel': 'e92f15f0fceb73e383b19864cfc0f60d'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 579,\n",
       "  'this_tel': '509af0f77adb5aa524efa26faa303d6e'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 580,\n",
       "  'this_tel': 'da000c584e979a959ff627dd338bd19c'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 581,\n",
       "  'this_tel': 'add735def352370b54b611b0af274ffc'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 582,\n",
       "  'this_tel': '32070fc93dd29124f79b05691fdd6194'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 583,\n",
       "  'this_tel': '36737a6454f0bd9c54b66cb24cd99059'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 584,\n",
       "  'this_tel': '317ae6bdbfb3c0fb08a410f936f312a5'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 585,\n",
       "  'this_tel': 'a7c73b469f191f80f28d2cdd10d1b350'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 586,\n",
       "  'this_tel': '1873b8fb45bced826f453d98cb34f1b9'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 587,\n",
       "  'this_tel': '65496d29d1bc4e448dcedea5270d090b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 588,\n",
       "  'this_tel': '75c29a61e7bc4edbf9cd8ca6a5700225'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 589,\n",
       "  'this_tel': 'e6b1af6e30eb55f968df5dad18ed06ca'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 590,\n",
       "  'this_tel': 'd389e44de2d8a7bcd015207a66041ff2'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 591,\n",
       "  'this_tel': '668c4590bbd9add9aa07e8b650660e10'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 592,\n",
       "  'this_tel': '2fa054198c0457a5e71d8208b0f07486'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 593,\n",
       "  'this_tel': 'd36fa40929b1f8432bbe41cedba6be88'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 594,\n",
       "  'this_tel': '8ef8fb045f20239d5571502015983813'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 595,\n",
       "  'this_tel': '7f0e4b0c2a2e9fe80cc1f91ae8002b2d'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 596,\n",
       "  'this_tel': '9f817a063b3ce4df8a3c542a7a94172b'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 597,\n",
       "  'this_tel': '2cbf98a57daf00598348b2713d803e5c'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 598,\n",
       "  'this_tel': 'ff8f29dc0ee3c557172c2d8bc5899ee2'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 599,\n",
       "  'this_tel': '70ceef8cb8d7badc7eb7ec3133200df3'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 600,\n",
       "  'this_tel': '2a58d1f0d5d3f8dd96c1e1db8e1b2fdb'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 601,\n",
       "  'this_tel': '5d6df9b8d1d1c23c50370c58d05e0a8e'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 602,\n",
       "  'this_tel': 'a9a8edb591ce583a63a35341f58157f9'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 603,\n",
       "  'this_tel': '195352c2c9e1731e1f89425c951ef414'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 604,\n",
       "  'this_tel': 'c769db84b715b37ed5a3413a60f9d07c'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 605,\n",
       "  'this_tel': 'dcc8a740a038183b95da8f1e5587ad76'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 606,\n",
       "  'this_tel': '52529d15654ac6bec737f9643944a4ed'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 607,\n",
       "  'this_tel': '07f6c381374a16b4009f119bfc2ed3ab'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 608,\n",
       "  'this_tel': 'bf4ea60bc9a1dbf877c6dbbc86cae6ba'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 609,\n",
       "  'this_tel': '28acae3cec911c0ed993c04886108982'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 610,\n",
       "  'this_tel': 'cc8b5b4214e63ca576ed4a31697d9b11'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 611,\n",
       "  'this_tel': '7f704dd1dd65b57fe9f6dffbe73a6151'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 612,\n",
       "  'this_tel': '1be018cc3864eb79e9a42b7bf810f9f1'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 613,\n",
       "  'this_tel': '950efcd17bfd1c64a01e17fd2f374b7b'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 614,\n",
       "  'this_tel': '6647af583068f90a3943ed6cb73a15d7'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 615,\n",
       "  'this_tel': '0972098cb169ef5713a22ed017b8cb31'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 616,\n",
       "  'this_tel': '421597a126d1b01d237f36ce2c80b1e2'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 617,\n",
       "  'this_tel': '103e799d4e406539f0568ac4afb493db'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 618,\n",
       "  'this_tel': '35d8db87b0b762ab9e37d629ee71f513'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 619,\n",
       "  'this_tel': 'fa027456957c3a7130cf98ab4b2dad7d'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 620,\n",
       "  'this_tel': 'a7ec3626e382cfb099030756b40724e3'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 621,\n",
       "  'this_tel': '8f73c388e6fe49050411090c4d286164'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 622,\n",
       "  'this_tel': 'ecb44a8ce332b3d33442a50a1417f492'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 623,\n",
       "  'this_tel': '828d7ac3f8297502a4dcdf51df40a72c'},\n",
       " {'salesstaff_id': 23,\n",
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       "  'customer_id': 1901,\n",
       "  'this_tel': '171aa42fd5d82a3ec6ce4f8e2cec5ab4'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1902,\n",
       "  'this_tel': '0cfeea3f9b19f8191d02fb25a3fb4e3f'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1903,\n",
       "  'this_tel': '1669a46f852681421d3d3eb6c783bb0e'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1904,\n",
       "  'this_tel': 'ecb50c547d2909d29b5172e7b54895e6'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1905,\n",
       "  'this_tel': 'ee6d3841534ab9b01868504955c80259'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1906,\n",
       "  'this_tel': 'fa74556a1cc2f7a4d578b874e25442c6'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1907,\n",
       "  'this_tel': 'bf22662dfa17b59851ab674be5972d7a'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1908,\n",
       "  'this_tel': '009f1b888c84f2098ee4df46147d644d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1909,\n",
       "  'this_tel': 'aa9ca00862677688225bb4c92192d51a'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1910,\n",
       "  'this_tel': '6c00a109001e9b4b6b52a4ccc45a298d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1911,\n",
       "  'this_tel': '346726de54e78e0f52079c360ce1332d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1912,\n",
       "  'this_tel': '359aa82f107ec2d83f985955908e2cdb'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1913,\n",
       "  'this_tel': 'abcfcd849ec632885d3b2b7f77ed9847'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1914,\n",
       "  'this_tel': 'a88938c44bd461c8e792af84abadf0ab'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1915,\n",
       "  'this_tel': '199bbbc91511d33e31a2ef260fbfa3b9'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1916,\n",
       "  'this_tel': '2406d6bdc978ced0f74c5c297ef195c5'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1917,\n",
       "  'this_tel': '1b6c7bf7aa3625bbae9731ad0ede0e66'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1918,\n",
       "  'this_tel': '37801301ca1796e612d03842c1b4533e'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1919,\n",
       "  'this_tel': 'da179f0b9048b0a694806b4e506191ef'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1920,\n",
       "  'this_tel': 'd6bcf234bcd4dace2aaabdbd6022e167'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1921,\n",
       "  'this_tel': 'e9a4344aaa9f4c8963bc70dd7e6059e5'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1922,\n",
       "  'this_tel': '08480393e6bbe319c8911d77bb02566d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1923,\n",
       "  'this_tel': '000907ea63cf5ace8d3aaa8c76e189e3'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1924,\n",
       "  'this_tel': '73c0c4fe51be8be90593f4aec48acf59'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1925,\n",
       "  'this_tel': '9d49f0c3ef14f1e6359a17978e510066'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1926,\n",
       "  'this_tel': 'd8cb2de891492d973096220b6fdeae9e'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1927,\n",
       "  'this_tel': 'ce7bff8ef5626b06945d69eb7326fc42'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1928,\n",
       "  'this_tel': 'e7d8be1569a4232645f4ce046a0757ea'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1929,\n",
       "  'this_tel': '317f274e6c0468ca0f03ebf0f2b329c0'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1930,\n",
       "  'this_tel': 'eae52196ab050f9bf4541578495fdb2d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1931,\n",
       "  'this_tel': '97eb457373e2239cd1fac3f5aceac22c'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1932,\n",
       "  'this_tel': 'f65d63641ab200b4aca68fca5e9edeec'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1933,\n",
       "  'this_tel': 'a68f36a95637a6bed6d5adbfb4d99201'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1934,\n",
       "  'this_tel': '9d5ec434d31a8f99ef2075e99da30ac1'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1935,\n",
       "  'this_tel': '66de4d4ecbc9d6d86c9e90c2978ca93d'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1936,\n",
       "  'this_tel': '1253e1fb3febee6bc58457e2aea7516f'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1937,\n",
       "  'this_tel': '8ea79bbaa18b54faaadbdffaca424a44'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1938,\n",
       "  'this_tel': '8ff09b09f91db839b5443fbd51291b8d'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1939,\n",
       "  'this_tel': '0f85afd84b68050a03a989d2b60fd110'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1940,\n",
       "  'this_tel': 'ce2c9c197dba3ace60579973e29f55ca'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1941,\n",
       "  'this_tel': '13d55d8f05f6aeea6468b7ecb7529fdb'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1942,\n",
       "  'this_tel': '0a36dcd7ca39b8a778fb12b51e944435'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1943,\n",
       "  'this_tel': '46b89b5727034e07c7d696e02bfed546'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1944,\n",
       "  'this_tel': 'b533af43acbaf861b1593268ea2b3754'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1945,\n",
       "  'this_tel': '1a0a613f5b769969609f407d7557440b'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1946,\n",
       "  'this_tel': '374abf6466e9e22f94cfe3a615f7a7fb'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1947,\n",
       "  'this_tel': '79de4951302b302c7a632ee98ae62ad2'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1948,\n",
       "  'this_tel': '3d015841ae37f7ad25374eb62640e2e4'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1949,\n",
       "  'this_tel': '798e52356e3fcb658b66afd831af6a50'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1950,\n",
       "  'this_tel': '44653fa9b8148e0a94615159f9c71548'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1951,\n",
       "  'this_tel': '886665a9f0ad41f77d21a6d297fd7e23'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1952,\n",
       "  'this_tel': '0fa786b31c799c2fede1febeebf97fa5'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1953,\n",
       "  'this_tel': '87fe09d91668525f3dfa57292f146de0'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1954,\n",
       "  'this_tel': '7a5bc79ee6c7bb095c3fc5a88b10d0c3'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1955,\n",
       "  'this_tel': 'fbd08ae1664510a260b113cb39aefd4f'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1956,\n",
       "  'this_tel': '424aaf97a3702d265fccf50027b74ca7'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1957,\n",
       "  'this_tel': 'b24b75a8b8f5d21b2f80875e8ae385a7'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1958,\n",
       "  'this_tel': '69cce487d25edd0f59eedf3f2be67fd2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1959,\n",
       "  'this_tel': '7c7898fa9faa6d9d7c799c27761f5dd4'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1960,\n",
       "  'this_tel': '9bdff46ac52db9fdb5ae46b4f804396d'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1961,\n",
       "  'this_tel': '38b1833da6f414348e4532407dad7e2b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1962,\n",
       "  'this_tel': '6e1532790a8e9acd7a4abe8cd7cf5bc2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1963,\n",
       "  'this_tel': 'd90da39f92d4da0a7154e601f17b7d06'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1964,\n",
       "  'this_tel': '7255d0259fc36091a45b96acde29c0d1'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1965,\n",
       "  'this_tel': '9dbdf11bf81e0d484edb87baa1730ce6'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1966,\n",
       "  'this_tel': '77bcf315d0f2ca4ceb4bfb2720866db5'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1967,\n",
       "  'this_tel': '1abc2ffaa27a0ecabf8e234a569129fe'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1968,\n",
       "  'this_tel': 'fda70f92058b222e033d7f1a0452a22a'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1969,\n",
       "  'this_tel': 'b1fed24d7cd289fba94774c9e2ea71e2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1970,\n",
       "  'this_tel': '2afd7ad7bdfaff169fd0913949ac2f05'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1971,\n",
       "  'this_tel': '89edd3cae503387351dde401e29f8d28'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1972,\n",
       "  'this_tel': '7c2fce6ddcfef539ff981143259bff37'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1973,\n",
       "  'this_tel': '991b5098cad30b739171e877e0daeb85'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1974,\n",
       "  'this_tel': 'd4bde39b3c5b854f413128f765a1a1f2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1975,\n",
       "  'this_tel': '152058fec98022084e9bb94dc8f45dfe'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1976,\n",
       "  'this_tel': 'dfd5e55f36726021f0f1ca6726ae5a7b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1977,\n",
       "  'this_tel': 'c4f58e0bd3c6b2b996be15d9b34fabd1'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1978,\n",
       "  'this_tel': '089fc83ae54e4b481c0b8ef24eacda8b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1979,\n",
       "  'this_tel': '2df48ad2643dbbba8009fe705c2fa2a1'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1980,\n",
       "  'this_tel': 'c913bff8bb629398479fad0bf8800f4f'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1981,\n",
       "  'this_tel': 'cae80e095f42a63eafeebb074bb19496'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1982,\n",
       "  'this_tel': '323fdb9c197edead876a9e4184f911aa'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1983,\n",
       "  'this_tel': 'c52e3b127847b8a4dd1576b54a78e11b'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1984,\n",
       "  'this_tel': 'bc9f933f78cf5b6c1da00cede735f9e2'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1985,\n",
       "  'this_tel': 'cfe3cd1fbc4716b5ba93043a59e40f53'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1986,\n",
       "  'this_tel': '59125551b82e8845ec6837ceb801cbaa'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1987,\n",
       "  'this_tel': '5928090122694c18756471f8fcd4431d'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1988,\n",
       "  'this_tel': '875f49e353cf7a89b72c5ea427939e8a'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1989,\n",
       "  'this_tel': 'c59c633aec2d34d3634a116d85fb1db6'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1990,\n",
       "  'this_tel': '28fdcc1e171c032eff04eb48324454c8'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1991,\n",
       "  'this_tel': '23d7f6de4e1e0d444259da4e049b05ad'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1992,\n",
       "  'this_tel': '9b80678ddee5d60e08e0a3ac636b09df'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1993,\n",
       "  'this_tel': '41373391b93d99b20b79ccaec8be9834'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1994,\n",
       "  'this_tel': '4c88c2fb7706f0d3b779832e2cace52e'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1995,\n",
       "  'this_tel': '7f0218bff51658a5018ce55c03bf6fc8'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1996,\n",
       "  'this_tel': 'f5d9866218060781e100d683bfbabd18'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1997,\n",
       "  'this_tel': '881ad60ec6f96d885ae91d45b9591211'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1998,\n",
       "  'this_tel': 'a72ef736c2e63e8a1f4221ea123b02b1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1999,\n",
       "  'this_tel': '8170ffdaba7520b4083a75a6e6795fe1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2000,\n",
       "  'this_tel': '8db2c679c2dea191586c630737dc99c3'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2001,\n",
       "  'this_tel': '951379d33f34d29ee42cdeac6b780cc1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2002,\n",
       "  'this_tel': '79fa1a88c3d8d6b3dc1265a6046c0441'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2003,\n",
       "  'this_tel': '2cdfdbebb50d21100899361b8e8a4dfd'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2004,\n",
       "  'this_tel': '2093cc6e7c8e9b7f41eb0c8d6bbe0ef6'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2005,\n",
       "  'this_tel': '0127f8fc0208c0794b3a2edbe2a158cc'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2006,\n",
       "  'this_tel': 'a0e586d19c6fe9846c03845530332bf9'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2007,\n",
       "  'this_tel': '345a7aa1097e4332e75abd98c7d4266b'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2008,\n",
       "  'this_tel': 'eb27e71ba048c098e99aaf4b2e4d3939'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2009,\n",
       "  'this_tel': '24c994e21abad0a8b91018e64e84a6e4'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2010,\n",
       "  'this_tel': '3e2b112516b8db3044c09c22d0279681'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2011,\n",
       "  'this_tel': '2b7d6eb47d8b60f4a0be62f7da778a0b'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2012,\n",
       "  'this_tel': 'dfa9b1aca944747c2ebc407484fce670'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2013,\n",
       "  'this_tel': '80a2b01f51603d87c2ba3f6114c703f9'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2014,\n",
       "  'this_tel': '6dda8572c1a36d369981882b2db05ff8'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2015,\n",
       "  'this_tel': '984fcdef13eec26f1977e67b149f58c8'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2016,\n",
       "  'this_tel': 'c8cd655d6170cb1750f1b614858439b2'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2017,\n",
       "  'this_tel': '8b7fb1b554721951a45bc38836530eb3'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2018,\n",
       "  'this_tel': 'b5ebf8a9057c2e5b5ec803d62c5fd75b'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2019,\n",
       "  'this_tel': 'f1ae8dd0675482d7822e9f24dee0e1ef'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2020,\n",
       "  'this_tel': 'b163e2fa72556ce719b4fc024106f9b5'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2021,\n",
       "  'this_tel': 'af8adfcbc8f08d2f891e4736acb2ed99'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2022,\n",
       "  'this_tel': 'e97c65c940cf4e0bd1b8e4f9763e67f8'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2023,\n",
       "  'this_tel': '67231e3bae7d077e86589b59395c700d'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2024,\n",
       "  'this_tel': '13067084c8eccdb885d702fdd64439c6'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2025,\n",
       "  'this_tel': 'dadfee8218ed42352a61e6ae47fb1ad9'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2026,\n",
       "  'this_tel': 'e49cf391b965eed0fcba646efcd4130e'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2027,\n",
       "  'this_tel': 'e5fd2d23e0e39aaa9a545cf2549a40ec'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2028,\n",
       "  'this_tel': 'f7bda5fb9459434bea7ef6f1dd2d3ac6'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2029,\n",
       "  'this_tel': '628316968d88351ee446579b1b5067c3'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2030,\n",
       "  'this_tel': 'fbf1bfe3c78192428900f44439f590c0'},\n",
       " {'salesstaff_id': 6,\n",
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       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2818,\n",
       "  'this_tel': 'f9987ccf0299dc9736b25a7cec0e47d9'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2819,\n",
       "  'this_tel': '665ce104e56b5261d7aa7e8b6148ff18'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2820,\n",
       "  'this_tel': '8e2cfeb61a622ac7402344e3d8159bdc'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2821,\n",
       "  'this_tel': 'ffe4e9fac583fd47d389b956b3054cec'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2822,\n",
       "  'this_tel': 'd000866ec07741c598e0d8cc7b560dfa'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2823,\n",
       "  'this_tel': '24021be75b09774725baf7851805f84c'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2824,\n",
       "  'this_tel': '2839a19710f6a9254c37fb2580cec16b'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2825,\n",
       "  'this_tel': '9b9082097fa396e71e9f603cc2e9f7ef'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2826,\n",
       "  'this_tel': '7b30f04535ae91e7aa98fc7def0c44be'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2827,\n",
       "  'this_tel': '2aee7799e7d0b955cdd6386408d4f623'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2828,\n",
       "  'this_tel': '5afca1f35deea67bf6c90575ebb3a7da'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2829,\n",
       "  'this_tel': 'b0f599c796786f6e5ed562add711d321'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2830,\n",
       "  'this_tel': 'db8cf07b000e94d123f5e55c093c07c3'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2831,\n",
       "  'this_tel': '68a26774e50f90433543f1aee588ed8f'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2832,\n",
       "  'this_tel': '8dc4adcf671b62ec70a26d357a2199f9'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2833,\n",
       "  'this_tel': '3dc7a564710146cd1d2bdcf24c11e8f3'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2834,\n",
       "  'this_tel': 'd5cebdb1f6da2f20c12049e03d719d2b'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3460,\n",
       "  'this_tel': 'd8a42fb03858efd797dfb1e453fd6fa9'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3461,\n",
       "  'this_tel': '134ff97725c05c417ade0b98f5acb782'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3462,\n",
       "  'this_tel': '82170f04b825000f46f8aca4dad8ccc7'}]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_mission_data1():\n",
    "    \"\"\"\n",
    "    [\n",
    "        {\"salesstaff_id\":id,\"customer_id\":id}\n",
    "    ]\n",
    "    \"\"\"\n",
    "    datas = []\n",
    "    df_customer_dict = df_customer.to_dict()\n",
    "    for index , salesstaff in enumerate(salesstaff_ids):\n",
    "        \n",
    "        \n",
    "        \n",
    "        for i in range(index*25,(index+1)*25):\n",
    "            \n",
    "            this_customer_id = df_customer_dict[\"customer_id\"][i]\n",
    "            this_tel = df_customer_dict[\"tel\"][i]\n",
    "            datas.append(\n",
    "            {\"salesstaff_id\":salesstaff,\n",
    "              \"customer_id\":this_customer_id,\n",
    "              \"this_tel\":this_tel\n",
    "            }\n",
    "            )\n",
    "    return datas\n",
    "#             print(salesstaff)\n",
    "#             print(this_customer_id)\n",
    "#             print(this_tel)\n",
    "\n",
    "datas1 = get_mission_data1()\n",
    "datas1\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>salesstaff_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>this_tel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>539</td>\n",
       "      <td>6f7602c534ce83d367b3c53a4f36c0b7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>540</td>\n",
       "      <td>d750c7b30e85efceb15f9838548fc085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>541</td>\n",
       "      <td>4fcd26ac2390e3f54d1a72b87ba4c77c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>542</td>\n",
       "      <td>7c134ea8df6ab6e78143eba0a3445e6e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>543</td>\n",
       "      <td>0c883e4a18c193c84e9c4785adb4d847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2</td>\n",
       "      <td>544</td>\n",
       "      <td>19de7741b9d2fb317b820984cd7b46dd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2</td>\n",
       "      <td>545</td>\n",
       "      <td>ec9817ef0722f3c76138dbc83228dc4c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2</td>\n",
       "      <td>546</td>\n",
       "      <td>3271d5953121d680d7dbd6dc636d3e5d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2</td>\n",
       "      <td>547</td>\n",
       "      <td>5ecdda7fe15c3714f848a4f3e877b335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>51267820d9645e83602584a17b31de10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>549</td>\n",
       "      <td>42ac663921f03535e93498584e213399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>550</td>\n",
       "      <td>28434be616a48e3afd41fad989618c59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2</td>\n",
       "      <td>551</td>\n",
       "      <td>bb291924c8ffd9ff2e44b1ed0f3f4ab3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>552</td>\n",
       "      <td>baf8047a1550beb98d4ec50f73dc68ef</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>553</td>\n",
       "      <td>684d2daf7e56a338a753a9f86406eab1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>554</td>\n",
       "      <td>a1b8ce7cb0a43f156e2eaed3bfe3a1de</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2</td>\n",
       "      <td>555</td>\n",
       "      <td>c74db03d9a6a4f8ba710ae90443ea5a7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>556</td>\n",
       "      <td>234277677a301203b2369544d52c40a6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2</td>\n",
       "      <td>557</td>\n",
       "      <td>dc50a84b1163f535cb5712627ad5074c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2</td>\n",
       "      <td>558</td>\n",
       "      <td>1365f5ae48dbedeb7a3eb77c544ec744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2</td>\n",
       "      <td>559</td>\n",
       "      <td>5c31eb0fe13a69cde0ed215a62916f2a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2</td>\n",
       "      <td>560</td>\n",
       "      <td>49583e3c50188987c3d4c7fa9e976ce8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2</td>\n",
       "      <td>561</td>\n",
       "      <td>b876d76916a8e59fcd3a3d93df1eb074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2</td>\n",
       "      <td>562</td>\n",
       "      <td>8c46781ac04196a16a12d1ab3558bafd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2</td>\n",
       "      <td>563</td>\n",
       "      <td>1207bb574951d508de0d767f41635326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>30</td>\n",
       "      <td>564</td>\n",
       "      <td>db606837d7882ce41033ae5cb4e3423a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>30</td>\n",
       "      <td>565</td>\n",
       "      <td>a06e1d9c5a8c1153a54e4afb9283989b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>30</td>\n",
       "      <td>566</td>\n",
       "      <td>a9eee1b73729a160607c5207d1564910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>30</td>\n",
       "      <td>567</td>\n",
       "      <td>0a107d4146b08e3c07cbe2732ba34412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>568</td>\n",
       "      <td>8894a3672eaf305ad6b8a910f0097e6d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>569</td>\n",
       "      <td>a8364563482cbf0abf68e0723a6e9dba</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>30</td>\n",
       "      <td>570</td>\n",
       "      <td>fac407cd3575f4e6582da2dbc8884d36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>30</td>\n",
       "      <td>571</td>\n",
       "      <td>6ccef8d221228afc009630d87edc1d3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>30</td>\n",
       "      <td>572</td>\n",
       "      <td>8c80d48fa13933118eee61784a57e520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>30</td>\n",
       "      <td>573</td>\n",
       "      <td>50059fc8ea6e4eddfe7fade624536a4b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>30</td>\n",
       "      <td>574</td>\n",
       "      <td>7e9c391cc6a253f16a58154db5c4fc54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>30</td>\n",
       "      <td>575</td>\n",
       "      <td>a8995d22e8f6d654593be1b128d8dba9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>30</td>\n",
       "      <td>576</td>\n",
       "      <td>7de85a1fc2f6a0713ebf8f6b51d64ec1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>30</td>\n",
       "      <td>577</td>\n",
       "      <td>aa985d8a9150f995bfaddcad6b0cd9df</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>30</td>\n",
       "      <td>578</td>\n",
       "      <td>e92f15f0fceb73e383b19864cfc0f60d</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>30</td>\n",
       "      <td>579</td>\n",
       "      <td>509af0f77adb5aa524efa26faa303d6e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>30</td>\n",
       "      <td>580</td>\n",
       "      <td>da000c584e979a959ff627dd338bd19c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>30</td>\n",
       "      <td>581</td>\n",
       "      <td>add735def352370b54b611b0af274ffc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>30</td>\n",
       "      <td>582</td>\n",
       "      <td>32070fc93dd29124f79b05691fdd6194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>30</td>\n",
       "      <td>583</td>\n",
       "      <td>36737a6454f0bd9c54b66cb24cd99059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>30</td>\n",
       "      <td>584</td>\n",
       "      <td>317ae6bdbfb3c0fb08a410f936f312a5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>30</td>\n",
       "      <td>585</td>\n",
       "      <td>a7c73b469f191f80f28d2cdd10d1b350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>30</td>\n",
       "      <td>586</td>\n",
       "      <td>1873b8fb45bced826f453d98cb34f1b9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>30</td>\n",
       "      <td>587</td>\n",
       "      <td>65496d29d1bc4e448dcedea5270d090b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>30</td>\n",
       "      <td>588</td>\n",
       "      <td>75c29a61e7bc4edbf9cd8ca6a5700225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    salesstaff_id  customer_id                          this_tel\n",
       "0               2          539  6f7602c534ce83d367b3c53a4f36c0b7\n",
       "1               2          540  d750c7b30e85efceb15f9838548fc085\n",
       "2               2          541  4fcd26ac2390e3f54d1a72b87ba4c77c\n",
       "3               2          542  7c134ea8df6ab6e78143eba0a3445e6e\n",
       "4               2          543  0c883e4a18c193c84e9c4785adb4d847\n",
       "5               2          544  19de7741b9d2fb317b820984cd7b46dd\n",
       "6               2          545  ec9817ef0722f3c76138dbc83228dc4c\n",
       "7               2          546  3271d5953121d680d7dbd6dc636d3e5d\n",
       "8               2          547  5ecdda7fe15c3714f848a4f3e877b335\n",
       "9               2          548  51267820d9645e83602584a17b31de10\n",
       "10              2          549  42ac663921f03535e93498584e213399\n",
       "11              2          550  28434be616a48e3afd41fad989618c59\n",
       "12              2          551  bb291924c8ffd9ff2e44b1ed0f3f4ab3\n",
       "13              2          552  baf8047a1550beb98d4ec50f73dc68ef\n",
       "14              2          553  684d2daf7e56a338a753a9f86406eab1\n",
       "15              2          554  a1b8ce7cb0a43f156e2eaed3bfe3a1de\n",
       "16              2          555  c74db03d9a6a4f8ba710ae90443ea5a7\n",
       "17              2          556  234277677a301203b2369544d52c40a6\n",
       "18              2          557  dc50a84b1163f535cb5712627ad5074c\n",
       "19              2          558  1365f5ae48dbedeb7a3eb77c544ec744\n",
       "20              2          559  5c31eb0fe13a69cde0ed215a62916f2a\n",
       "21              2          560  49583e3c50188987c3d4c7fa9e976ce8\n",
       "22              2          561  b876d76916a8e59fcd3a3d93df1eb074\n",
       "23              2          562  8c46781ac04196a16a12d1ab3558bafd\n",
       "24              2          563  1207bb574951d508de0d767f41635326\n",
       "25             30          564  db606837d7882ce41033ae5cb4e3423a\n",
       "26             30          565  a06e1d9c5a8c1153a54e4afb9283989b\n",
       "27             30          566  a9eee1b73729a160607c5207d1564910\n",
       "28             30          567  0a107d4146b08e3c07cbe2732ba34412\n",
       "29             30          568  8894a3672eaf305ad6b8a910f0097e6d\n",
       "30             30          569  a8364563482cbf0abf68e0723a6e9dba\n",
       "31             30          570  fac407cd3575f4e6582da2dbc8884d36\n",
       "32             30          571  6ccef8d221228afc009630d87edc1d3c\n",
       "33             30          572  8c80d48fa13933118eee61784a57e520\n",
       "34             30          573  50059fc8ea6e4eddfe7fade624536a4b\n",
       "35             30          574  7e9c391cc6a253f16a58154db5c4fc54\n",
       "36             30          575  a8995d22e8f6d654593be1b128d8dba9\n",
       "37             30          576  7de85a1fc2f6a0713ebf8f6b51d64ec1\n",
       "38             30          577  aa985d8a9150f995bfaddcad6b0cd9df\n",
       "39             30          578  e92f15f0fceb73e383b19864cfc0f60d\n",
       "40             30          579  509af0f77adb5aa524efa26faa303d6e\n",
       "41             30          580  da000c584e979a959ff627dd338bd19c\n",
       "42             30          581  add735def352370b54b611b0af274ffc\n",
       "43             30          582  32070fc93dd29124f79b05691fdd6194\n",
       "44             30          583  36737a6454f0bd9c54b66cb24cd99059\n",
       "45             30          584  317ae6bdbfb3c0fb08a410f936f312a5\n",
       "46             30          585  a7c73b469f191f80f28d2cdd10d1b350\n",
       "47             30          586  1873b8fb45bced826f453d98cb34f1b9\n",
       "48             30          587  65496d29d1bc4e448dcedea5270d090b\n",
       "49             30          588  75c29a61e7bc4edbf9cd8ca6a5700225"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_a = pd.DataFrame(datas1)\n",
    "df_a.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>tel</th>\n",
       "      <th>salesstaff_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12231</td>\n",
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       "      <td>4</td>\n",
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       "      <th>1</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29892</td>\n",
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       "      <td>8</td>\n",
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       "      <th>4</th>\n",
       "      <td>17229</td>\n",
       "      <td>486ea018b00323972c871097b9736a26</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id                               tel  salesstaff_id\n",
       "0        12231  17810ad73067e8706f5b67f2ec8834fa              4\n",
       "1        12231  17810ad73067e8706f5b67f2ec8834fa              8\n",
       "2        12231  17810ad73067e8706f5b67f2ec8834fa             26\n",
       "3        29892  478d1ac970fbdbeaa1eb57d419c35e72              8\n",
       "4        17229  486ea018b00323972c871097b9736a26              8"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sql3 = 'select mission.customer_id as customer_id, c.tel as tel, mission.salesstaff_id as salesstaff_id from mission inner join customer c on mission.customer_id = c.id where customer_id in (select customer_id from  mission where createDate = \"2020-06-29\" and status_id =1);'\n",
    "\n",
    "df_last_mission = pd.read_sql(\n",
    "sql3,conn)\n",
    "\n",
    "df_last_mission.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for customer_id ,groupby_customerid in df_last_mission:\n",
    "#         print(customer_id ,groupby_customerid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2,\n",
       " 30,\n",
       " 14,\n",
       " 23,\n",
       " 16,\n",
       " 3,\n",
       " 25,\n",
       " 12,\n",
       " 28,\n",
       " 22,\n",
       " 29,\n",
       " 8,\n",
       " 19,\n",
       " 26,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 11,\n",
       " 6,\n",
       " 13,\n",
       " 15,\n",
       " 4,\n",
       " 18,\n",
       " 17,\n",
       " 20,\n",
       " 1,\n",
       " 5,\n",
       " 7,\n",
       " 10,\n",
       " 9]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salesstaff_ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>tel</th>\n",
       "      <th>salesstaff_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>29892</td>\n",
       "      <td>478d1ac970fbdbeaa1eb57d419c35e72</td>\n",
       "      <td>8</td>\n",
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       "      <th>4</th>\n",
       "      <td>17229</td>\n",
       "      <td>486ea018b00323972c871097b9736a26</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id                               tel  salesstaff_id\n",
       "0        12231  17810ad73067e8706f5b67f2ec8834fa              4\n",
       "1        12231  17810ad73067e8706f5b67f2ec8834fa              8\n",
       "2        12231  17810ad73067e8706f5b67f2ec8834fa             26\n",
       "3        29892  478d1ac970fbdbeaa1eb57d419c35e72              8\n",
       "4        17229  486ea018b00323972c871097b9736a26              8"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_last_mission.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2,\n",
       " 30,\n",
       " 14,\n",
       " 23,\n",
       " 16,\n",
       " 3,\n",
       " 25,\n",
       " 12,\n",
       " 28,\n",
       " 22,\n",
       " 29,\n",
       " 8,\n",
       " 19,\n",
       " 26,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 11,\n",
       " 6,\n",
       " 13,\n",
       " 15,\n",
       " 4,\n",
       " 18,\n",
       " 17,\n",
       " 20,\n",
       " 1,\n",
       " 5,\n",
       " 7,\n",
       " 10,\n",
       " 9]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df_salesstaff[\"id\"].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.groupby.generic.DataFrameGroupBy"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# type(df_last_mission.groupby(\"customer_id\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>tel</th>\n",
       "      <th>salesstaff_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>478d1ac970fbdbeaa1eb57d419c35e72</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>486ea018b00323972c871097b9736a26</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>9bd44152af39ce4a2163b40366602bdc</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6</td>\n",
       "      <td>fd9b27f03f6cb940ccf29efaf55cd88a</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4</td>\n",
       "      <td>a721b7b220d7e355cd789bfff0549e3f</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4</td>\n",
       "      <td>82d0bd71c6dbd4a1005405c6e9eb6a0d</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4</td>\n",
       "      <td>01532afa1d63e8975a244c7259307aaf</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4</td>\n",
       "      <td>8568a35d3db80be71df99645df0dc8e1</td>\n",
       "      <td>18</td>\n",
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       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>6</td>\n",
       "      <td>0ac238c0162649b78d35dfc08fcae309</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>6</td>\n",
       "      <td>2354e260860a3d2f9ddb7b664303110c</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>5</td>\n",
       "      <td>3ec078b9beb80574311af95c41fbfbc4</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>6</td>\n",
       "      <td>23b9216d0a9ae32aaeaa6e7a17f0971f</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>6</td>\n",
       "      <td>715cd24adf27d9268ca44ea00937bebe</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>5</td>\n",
       "      <td>dd0d1c93c8a05fc65f0bab0ed24334a9</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>5</td>\n",
       "      <td>a12ddddece31a06b674e41d00c120a35</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>321</th>\n",
       "      <td>5</td>\n",
       "      <td>9569b787c5f00f92f1040ef22c43144f</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>5</td>\n",
       "      <td>25f890253794de931f2ada10cfb7e173</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     customer_id                               tel  salesstaff_id\n",
       "0              1  17810ad73067e8706f5b67f2ec8834fa              4\n",
       "1              1  17810ad73067e8706f5b67f2ec8834fa              8\n",
       "2              4  17810ad73067e8706f5b67f2ec8834fa             26\n",
       "3              1  478d1ac970fbdbeaa1eb57d419c35e72              8\n",
       "4              1  486ea018b00323972c871097b9736a26              8\n",
       "5              1  9bd44152af39ce4a2163b40366602bdc              8\n",
       "9              6  fd9b27f03f6cb940ccf29efaf55cd88a             20\n",
       "15             4  a721b7b220d7e355cd789bfff0549e3f             30\n",
       "19             4  82d0bd71c6dbd4a1005405c6e9eb6a0d             10\n",
       "23             4  01532afa1d63e8975a244c7259307aaf             13\n",
       "27             4  8568a35d3db80be71df99645df0dc8e1             18\n",
       "34             6  0ac238c0162649b78d35dfc08fcae309             29\n",
       "52             6  2354e260860a3d2f9ddb7b664303110c             26\n",
       "61             5  3ec078b9beb80574311af95c41fbfbc4             13\n",
       "77             6  23b9216d0a9ae32aaeaa6e7a17f0971f             20\n",
       "82             6  715cd24adf27d9268ca44ea00937bebe             29\n",
       "170            5  dd0d1c93c8a05fc65f0bab0ed24334a9             11\n",
       "244            5  a12ddddece31a06b674e41d00c120a35             11\n",
       "321            5  9569b787c5f00f92f1040ef22c43144f              1\n",
       "460            5  25f890253794de931f2ada10cfb7e173              5"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df_last_mission.groupby(by=\"customer_id\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'DataFrameGroupBy' object has no attribute 'values'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-17-9d54d0e2a090>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf_last_mission\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"customer_id\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\core\\groupby\\groupby.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, attr)\u001b[0m\n\u001b[0;32m    578\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    579\u001b[0m         raise AttributeError(\n\u001b[1;32m--> 580\u001b[1;33m             \u001b[1;34mf\"'{type(self).__name__}' object has no attribute '{attr}'\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    581\u001b[0m         )\n\u001b[0;32m    582\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'DataFrameGroupBy' object has no attribute 'values'"
     ]
    }
   ],
   "source": [
    "# df_last_mission.groupby(\"customer_id\").values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customer_id</th>\n",
       "      <th>tel</th>\n",
       "      <th>salesstaff_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12231</td>\n",
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       "      <td>4</td>\n",
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       "      <th>1</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12231</td>\n",
       "      <td>17810ad73067e8706f5b67f2ec8834fa</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29892</td>\n",
       "      <td>478d1ac970fbdbeaa1eb57d419c35e72</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17229</td>\n",
       "      <td>486ea018b00323972c871097b9736a26</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customer_id                               tel  salesstaff_id\n",
       "0        12231  17810ad73067e8706f5b67f2ec8834fa              4\n",
       "1        12231  17810ad73067e8706f5b67f2ec8834fa              8\n",
       "2        12231  17810ad73067e8706f5b67f2ec8834fa             26\n",
       "3        29892  478d1ac970fbdbeaa1eb57d419c35e72              8\n",
       "4        17229  486ea018b00323972c871097b9736a26              8"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_last_mission.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30}\n",
      "487\n",
      "---->\n",
      "     customer_id                               tel  salesstaff_id\n",
      "242          487  a12ddddece31a06b674e41d00c120a35             24\n",
      "243          487  a12ddddece31a06b674e41d00c120a35             13\n",
      "244          487  a12ddddece31a06b674e41d00c120a35             11\n",
      "---->\n",
      "{24, 11, 13}\n",
      "30\n"
     ]
    }
   ],
   "source": [
    "def get_mission_data2():\n",
    "    cache_salesstaff_ids = set(salesstaff_ids)\n",
    "    print(cache_salesstaff_ids)\n",
    "    for customer_id ,groupby_customerid in df_last_mission.groupby(\"customer_id\"):\n",
    "#         print(customer_id ,groupby_customerid)\n",
    "        print(customer_id)\n",
    "        print(\"---->\")\n",
    "        print(groupby_customerid)\n",
    "        print(\"---->\")\n",
    "        print(set(groupby_customerid[\"salesstaff_id\"].values.tolist()))\n",
    "        \n",
    "        a = random.choice(\n",
    "            list(\n",
    "                cache_salesstaff_ids - set(groupby_customerid[\"salesstaff_id\"].values.tolist())\n",
    "            )\n",
    "        ) \n",
    "        print(a)\n",
    "        break\n",
    "        \n",
    "get_mission_data2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = [1,2,3,4]\n",
    "random.choice(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2, 4}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = {1,2,3,4}\n",
    "b = {1,3,5}\n",
    "a-b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'salesstaff_id': 5,\n",
       "  'custmer_id': 487,\n",
       "  'tel': 'a12ddddece31a06b674e41d00c120a35'}]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_mission_data2():\n",
    "    datas = []\n",
    "    cache_salesstaff_ids = set(salesstaff_ids)\n",
    "#     print(cache_salesstaff_ids)\n",
    "    for customer_id ,groupby_customerid in df_last_mission.groupby(\"customer_id\"):\n",
    "        \n",
    "        # telphone\n",
    "        tel = groupby_customerid[\"tel\"].iloc[0]\n",
    "        cache2_salesstaff_ids = list(\n",
    "            cache_salesstaff_ids -  set(groupby_customerid[\"salesstaff_id\"].values.tolist())\n",
    "        )\n",
    "        \n",
    "#         print(cache2_salesstaff_ids)\n",
    "        if not cache2_salesstaff_ids :\n",
    "            cache_salesstaff_ids = set(salesstaff_ids)\n",
    "            \n",
    "            cache2_salesstaff_ids = list(\n",
    "                cache_salesstaff_ids -  set(groupby_customerid[\"salesstaff_id\"].values.tolist())\n",
    "            )\n",
    "                \n",
    "#         print(customer_id ,groupby_customerid)\n",
    "                \n",
    "        # salesstaff id\n",
    "        choice_salesstaff_id = random.choice(\n",
    "                cache2_salesstaff_ids \n",
    "        )\n",
    "        \n",
    "        cache_salesstaff_ids = cache_salesstaff_ids - set([choice_salesstaff_id])\n",
    "        \n",
    "        datas.append(\n",
    "            {\n",
    "                \"salesstaff_id\":choice_salesstaff_id,\n",
    "                \"custmer_id\":customer_id,\n",
    "                \"tel\":tel,\n",
    "                \n",
    "            }\n",
    "        \n",
    "        )\n",
    "        return datas\n",
    "        \n",
    "datas2 = get_mission_data2()\n",
    "datas2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_total = datas1+datas2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'salesstaff_id': 2,\n",
       "  'customer_id': 539,\n",
       "  'this_tel': '6f7602c534ce83d367b3c53a4f36c0b7'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 540,\n",
       "  'this_tel': 'd750c7b30e85efceb15f9838548fc085'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 541,\n",
       "  'this_tel': '4fcd26ac2390e3f54d1a72b87ba4c77c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 542,\n",
       "  'this_tel': '7c134ea8df6ab6e78143eba0a3445e6e'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 543,\n",
       "  'this_tel': '0c883e4a18c193c84e9c4785adb4d847'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 544,\n",
       "  'this_tel': '19de7741b9d2fb317b820984cd7b46dd'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 545,\n",
       "  'this_tel': 'ec9817ef0722f3c76138dbc83228dc4c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 546,\n",
       "  'this_tel': '3271d5953121d680d7dbd6dc636d3e5d'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 547,\n",
       "  'this_tel': '5ecdda7fe15c3714f848a4f3e877b335'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 548,\n",
       "  'this_tel': '51267820d9645e83602584a17b31de10'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 549,\n",
       "  'this_tel': '42ac663921f03535e93498584e213399'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 550,\n",
       "  'this_tel': '28434be616a48e3afd41fad989618c59'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 551,\n",
       "  'this_tel': 'bb291924c8ffd9ff2e44b1ed0f3f4ab3'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 552,\n",
       "  'this_tel': 'baf8047a1550beb98d4ec50f73dc68ef'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 553,\n",
       "  'this_tel': '684d2daf7e56a338a753a9f86406eab1'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 554,\n",
       "  'this_tel': 'a1b8ce7cb0a43f156e2eaed3bfe3a1de'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 555,\n",
       "  'this_tel': 'c74db03d9a6a4f8ba710ae90443ea5a7'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 556,\n",
       "  'this_tel': '234277677a301203b2369544d52c40a6'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 557,\n",
       "  'this_tel': 'dc50a84b1163f535cb5712627ad5074c'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 558,\n",
       "  'this_tel': '1365f5ae48dbedeb7a3eb77c544ec744'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 559,\n",
       "  'this_tel': '5c31eb0fe13a69cde0ed215a62916f2a'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 560,\n",
       "  'this_tel': '49583e3c50188987c3d4c7fa9e976ce8'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 561,\n",
       "  'this_tel': 'b876d76916a8e59fcd3a3d93df1eb074'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 562,\n",
       "  'this_tel': '8c46781ac04196a16a12d1ab3558bafd'},\n",
       " {'salesstaff_id': 2,\n",
       "  'customer_id': 563,\n",
       "  'this_tel': '1207bb574951d508de0d767f41635326'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 564,\n",
       "  'this_tel': 'db606837d7882ce41033ae5cb4e3423a'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 565,\n",
       "  'this_tel': 'a06e1d9c5a8c1153a54e4afb9283989b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 566,\n",
       "  'this_tel': 'a9eee1b73729a160607c5207d1564910'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 567,\n",
       "  'this_tel': '0a107d4146b08e3c07cbe2732ba34412'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 568,\n",
       "  'this_tel': '8894a3672eaf305ad6b8a910f0097e6d'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 569,\n",
       "  'this_tel': 'a8364563482cbf0abf68e0723a6e9dba'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 570,\n",
       "  'this_tel': 'fac407cd3575f4e6582da2dbc8884d36'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 571,\n",
       "  'this_tel': '6ccef8d221228afc009630d87edc1d3c'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 572,\n",
       "  'this_tel': '8c80d48fa13933118eee61784a57e520'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 573,\n",
       "  'this_tel': '50059fc8ea6e4eddfe7fade624536a4b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 574,\n",
       "  'this_tel': '7e9c391cc6a253f16a58154db5c4fc54'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 575,\n",
       "  'this_tel': 'a8995d22e8f6d654593be1b128d8dba9'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 576,\n",
       "  'this_tel': '7de85a1fc2f6a0713ebf8f6b51d64ec1'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 577,\n",
       "  'this_tel': 'aa985d8a9150f995bfaddcad6b0cd9df'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 578,\n",
       "  'this_tel': 'e92f15f0fceb73e383b19864cfc0f60d'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 579,\n",
       "  'this_tel': '509af0f77adb5aa524efa26faa303d6e'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 580,\n",
       "  'this_tel': 'da000c584e979a959ff627dd338bd19c'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 581,\n",
       "  'this_tel': 'add735def352370b54b611b0af274ffc'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 582,\n",
       "  'this_tel': '32070fc93dd29124f79b05691fdd6194'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 583,\n",
       "  'this_tel': '36737a6454f0bd9c54b66cb24cd99059'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 584,\n",
       "  'this_tel': '317ae6bdbfb3c0fb08a410f936f312a5'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 585,\n",
       "  'this_tel': 'a7c73b469f191f80f28d2cdd10d1b350'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 586,\n",
       "  'this_tel': '1873b8fb45bced826f453d98cb34f1b9'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 587,\n",
       "  'this_tel': '65496d29d1bc4e448dcedea5270d090b'},\n",
       " {'salesstaff_id': 30,\n",
       "  'customer_id': 588,\n",
       "  'this_tel': '75c29a61e7bc4edbf9cd8ca6a5700225'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 589,\n",
       "  'this_tel': 'e6b1af6e30eb55f968df5dad18ed06ca'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 590,\n",
       "  'this_tel': 'd389e44de2d8a7bcd015207a66041ff2'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 591,\n",
       "  'this_tel': '668c4590bbd9add9aa07e8b650660e10'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 592,\n",
       "  'this_tel': '2fa054198c0457a5e71d8208b0f07486'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 593,\n",
       "  'this_tel': 'd36fa40929b1f8432bbe41cedba6be88'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 594,\n",
       "  'this_tel': '8ef8fb045f20239d5571502015983813'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 595,\n",
       "  'this_tel': '7f0e4b0c2a2e9fe80cc1f91ae8002b2d'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 596,\n",
       "  'this_tel': '9f817a063b3ce4df8a3c542a7a94172b'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 597,\n",
       "  'this_tel': '2cbf98a57daf00598348b2713d803e5c'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 598,\n",
       "  'this_tel': 'ff8f29dc0ee3c557172c2d8bc5899ee2'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 599,\n",
       "  'this_tel': '70ceef8cb8d7badc7eb7ec3133200df3'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 600,\n",
       "  'this_tel': '2a58d1f0d5d3f8dd96c1e1db8e1b2fdb'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 601,\n",
       "  'this_tel': '5d6df9b8d1d1c23c50370c58d05e0a8e'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 602,\n",
       "  'this_tel': 'a9a8edb591ce583a63a35341f58157f9'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 603,\n",
       "  'this_tel': '195352c2c9e1731e1f89425c951ef414'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 604,\n",
       "  'this_tel': 'c769db84b715b37ed5a3413a60f9d07c'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 605,\n",
       "  'this_tel': 'dcc8a740a038183b95da8f1e5587ad76'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 606,\n",
       "  'this_tel': '52529d15654ac6bec737f9643944a4ed'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 607,\n",
       "  'this_tel': '07f6c381374a16b4009f119bfc2ed3ab'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 608,\n",
       "  'this_tel': 'bf4ea60bc9a1dbf877c6dbbc86cae6ba'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 609,\n",
       "  'this_tel': '28acae3cec911c0ed993c04886108982'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 610,\n",
       "  'this_tel': 'cc8b5b4214e63ca576ed4a31697d9b11'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 611,\n",
       "  'this_tel': '7f704dd1dd65b57fe9f6dffbe73a6151'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 612,\n",
       "  'this_tel': '1be018cc3864eb79e9a42b7bf810f9f1'},\n",
       " {'salesstaff_id': 14,\n",
       "  'customer_id': 613,\n",
       "  'this_tel': '950efcd17bfd1c64a01e17fd2f374b7b'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 614,\n",
       "  'this_tel': '6647af583068f90a3943ed6cb73a15d7'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 615,\n",
       "  'this_tel': '0972098cb169ef5713a22ed017b8cb31'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 616,\n",
       "  'this_tel': '421597a126d1b01d237f36ce2c80b1e2'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 617,\n",
       "  'this_tel': '103e799d4e406539f0568ac4afb493db'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 618,\n",
       "  'this_tel': '35d8db87b0b762ab9e37d629ee71f513'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 619,\n",
       "  'this_tel': 'fa027456957c3a7130cf98ab4b2dad7d'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 620,\n",
       "  'this_tel': 'a7ec3626e382cfb099030756b40724e3'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 621,\n",
       "  'this_tel': '8f73c388e6fe49050411090c4d286164'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 622,\n",
       "  'this_tel': 'ecb44a8ce332b3d33442a50a1417f492'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 623,\n",
       "  'this_tel': '828d7ac3f8297502a4dcdf51df40a72c'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 624,\n",
       "  'this_tel': 'ea1c9e9d8eab8d0240396d80db18db12'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 625,\n",
       "  'this_tel': 'ad9e2773dcacb3ccb9de07fc84ea855e'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 626,\n",
       "  'this_tel': '3ff5059da7d708d6025ee02e138f1cb7'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 627,\n",
       "  'this_tel': '32dafc73881ddd6e24c16fdf07f89e31'},\n",
       " {'salesstaff_id': 23,\n",
       "  'customer_id': 628,\n",
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       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1906,\n",
       "  'this_tel': 'fa74556a1cc2f7a4d578b874e25442c6'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1907,\n",
       "  'this_tel': 'bf22662dfa17b59851ab674be5972d7a'},\n",
       " {'salesstaff_id': 26,\n",
       "  'customer_id': 1908,\n",
       "  'this_tel': '009f1b888c84f2098ee4df46147d644d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1909,\n",
       "  'this_tel': 'aa9ca00862677688225bb4c92192d51a'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1910,\n",
       "  'this_tel': '6c00a109001e9b4b6b52a4ccc45a298d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1911,\n",
       "  'this_tel': '346726de54e78e0f52079c360ce1332d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1912,\n",
       "  'this_tel': '359aa82f107ec2d83f985955908e2cdb'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1913,\n",
       "  'this_tel': 'abcfcd849ec632885d3b2b7f77ed9847'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1914,\n",
       "  'this_tel': 'a88938c44bd461c8e792af84abadf0ab'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1915,\n",
       "  'this_tel': '199bbbc91511d33e31a2ef260fbfa3b9'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1916,\n",
       "  'this_tel': '2406d6bdc978ced0f74c5c297ef195c5'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1917,\n",
       "  'this_tel': '1b6c7bf7aa3625bbae9731ad0ede0e66'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1918,\n",
       "  'this_tel': '37801301ca1796e612d03842c1b4533e'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1919,\n",
       "  'this_tel': 'da179f0b9048b0a694806b4e506191ef'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1920,\n",
       "  'this_tel': 'd6bcf234bcd4dace2aaabdbd6022e167'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1921,\n",
       "  'this_tel': 'e9a4344aaa9f4c8963bc70dd7e6059e5'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1922,\n",
       "  'this_tel': '08480393e6bbe319c8911d77bb02566d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1923,\n",
       "  'this_tel': '000907ea63cf5ace8d3aaa8c76e189e3'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1924,\n",
       "  'this_tel': '73c0c4fe51be8be90593f4aec48acf59'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1925,\n",
       "  'this_tel': '9d49f0c3ef14f1e6359a17978e510066'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1926,\n",
       "  'this_tel': 'd8cb2de891492d973096220b6fdeae9e'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1927,\n",
       "  'this_tel': 'ce7bff8ef5626b06945d69eb7326fc42'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1928,\n",
       "  'this_tel': 'e7d8be1569a4232645f4ce046a0757ea'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1929,\n",
       "  'this_tel': '317f274e6c0468ca0f03ebf0f2b329c0'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1930,\n",
       "  'this_tel': 'eae52196ab050f9bf4541578495fdb2d'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1931,\n",
       "  'this_tel': '97eb457373e2239cd1fac3f5aceac22c'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1932,\n",
       "  'this_tel': 'f65d63641ab200b4aca68fca5e9edeec'},\n",
       " {'salesstaff_id': 21,\n",
       "  'customer_id': 1933,\n",
       "  'this_tel': 'a68f36a95637a6bed6d5adbfb4d99201'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1934,\n",
       "  'this_tel': '9d5ec434d31a8f99ef2075e99da30ac1'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1935,\n",
       "  'this_tel': '66de4d4ecbc9d6d86c9e90c2978ca93d'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1936,\n",
       "  'this_tel': '1253e1fb3febee6bc58457e2aea7516f'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1937,\n",
       "  'this_tel': '8ea79bbaa18b54faaadbdffaca424a44'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1938,\n",
       "  'this_tel': '8ff09b09f91db839b5443fbd51291b8d'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1939,\n",
       "  'this_tel': '0f85afd84b68050a03a989d2b60fd110'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1940,\n",
       "  'this_tel': 'ce2c9c197dba3ace60579973e29f55ca'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1941,\n",
       "  'this_tel': '13d55d8f05f6aeea6468b7ecb7529fdb'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1942,\n",
       "  'this_tel': '0a36dcd7ca39b8a778fb12b51e944435'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1943,\n",
       "  'this_tel': '46b89b5727034e07c7d696e02bfed546'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1944,\n",
       "  'this_tel': 'b533af43acbaf861b1593268ea2b3754'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1945,\n",
       "  'this_tel': '1a0a613f5b769969609f407d7557440b'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1946,\n",
       "  'this_tel': '374abf6466e9e22f94cfe3a615f7a7fb'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1947,\n",
       "  'this_tel': '79de4951302b302c7a632ee98ae62ad2'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1948,\n",
       "  'this_tel': '3d015841ae37f7ad25374eb62640e2e4'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1949,\n",
       "  'this_tel': '798e52356e3fcb658b66afd831af6a50'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1950,\n",
       "  'this_tel': '44653fa9b8148e0a94615159f9c71548'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1951,\n",
       "  'this_tel': '886665a9f0ad41f77d21a6d297fd7e23'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1952,\n",
       "  'this_tel': '0fa786b31c799c2fede1febeebf97fa5'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1953,\n",
       "  'this_tel': '87fe09d91668525f3dfa57292f146de0'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1954,\n",
       "  'this_tel': '7a5bc79ee6c7bb095c3fc5a88b10d0c3'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1955,\n",
       "  'this_tel': 'fbd08ae1664510a260b113cb39aefd4f'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1956,\n",
       "  'this_tel': '424aaf97a3702d265fccf50027b74ca7'},\n",
       " {'salesstaff_id': 24,\n",
       "  'customer_id': 1957,\n",
       "  'this_tel': 'b24b75a8b8f5d21b2f80875e8ae385a7'},\n",
       " {'salesstaff_id': 24,\n",
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       "  'this_tel': '69cce487d25edd0f59eedf3f2be67fd2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1959,\n",
       "  'this_tel': '7c7898fa9faa6d9d7c799c27761f5dd4'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1960,\n",
       "  'this_tel': '9bdff46ac52db9fdb5ae46b4f804396d'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1961,\n",
       "  'this_tel': '38b1833da6f414348e4532407dad7e2b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1962,\n",
       "  'this_tel': '6e1532790a8e9acd7a4abe8cd7cf5bc2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1963,\n",
       "  'this_tel': 'd90da39f92d4da0a7154e601f17b7d06'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1964,\n",
       "  'this_tel': '7255d0259fc36091a45b96acde29c0d1'},\n",
       " {'salesstaff_id': 27,\n",
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       "  'this_tel': '9dbdf11bf81e0d484edb87baa1730ce6'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1966,\n",
       "  'this_tel': '77bcf315d0f2ca4ceb4bfb2720866db5'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1967,\n",
       "  'this_tel': '1abc2ffaa27a0ecabf8e234a569129fe'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1968,\n",
       "  'this_tel': 'fda70f92058b222e033d7f1a0452a22a'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1969,\n",
       "  'this_tel': 'b1fed24d7cd289fba94774c9e2ea71e2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1970,\n",
       "  'this_tel': '2afd7ad7bdfaff169fd0913949ac2f05'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1971,\n",
       "  'this_tel': '89edd3cae503387351dde401e29f8d28'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1972,\n",
       "  'this_tel': '7c2fce6ddcfef539ff981143259bff37'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1973,\n",
       "  'this_tel': '991b5098cad30b739171e877e0daeb85'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1974,\n",
       "  'this_tel': 'd4bde39b3c5b854f413128f765a1a1f2'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1975,\n",
       "  'this_tel': '152058fec98022084e9bb94dc8f45dfe'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1976,\n",
       "  'this_tel': 'dfd5e55f36726021f0f1ca6726ae5a7b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1977,\n",
       "  'this_tel': 'c4f58e0bd3c6b2b996be15d9b34fabd1'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1978,\n",
       "  'this_tel': '089fc83ae54e4b481c0b8ef24eacda8b'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1979,\n",
       "  'this_tel': '2df48ad2643dbbba8009fe705c2fa2a1'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1980,\n",
       "  'this_tel': 'c913bff8bb629398479fad0bf8800f4f'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1981,\n",
       "  'this_tel': 'cae80e095f42a63eafeebb074bb19496'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1982,\n",
       "  'this_tel': '323fdb9c197edead876a9e4184f911aa'},\n",
       " {'salesstaff_id': 27,\n",
       "  'customer_id': 1983,\n",
       "  'this_tel': 'c52e3b127847b8a4dd1576b54a78e11b'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1984,\n",
       "  'this_tel': 'bc9f933f78cf5b6c1da00cede735f9e2'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1985,\n",
       "  'this_tel': 'cfe3cd1fbc4716b5ba93043a59e40f53'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1986,\n",
       "  'this_tel': '59125551b82e8845ec6837ceb801cbaa'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1987,\n",
       "  'this_tel': '5928090122694c18756471f8fcd4431d'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1988,\n",
       "  'this_tel': '875f49e353cf7a89b72c5ea427939e8a'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1989,\n",
       "  'this_tel': 'c59c633aec2d34d3634a116d85fb1db6'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1990,\n",
       "  'this_tel': '28fdcc1e171c032eff04eb48324454c8'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1991,\n",
       "  'this_tel': '23d7f6de4e1e0d444259da4e049b05ad'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1992,\n",
       "  'this_tel': '9b80678ddee5d60e08e0a3ac636b09df'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1993,\n",
       "  'this_tel': '41373391b93d99b20b79ccaec8be9834'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1994,\n",
       "  'this_tel': '4c88c2fb7706f0d3b779832e2cace52e'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1995,\n",
       "  'this_tel': '7f0218bff51658a5018ce55c03bf6fc8'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1996,\n",
       "  'this_tel': 'f5d9866218060781e100d683bfbabd18'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1997,\n",
       "  'this_tel': '881ad60ec6f96d885ae91d45b9591211'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1998,\n",
       "  'this_tel': 'a72ef736c2e63e8a1f4221ea123b02b1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 1999,\n",
       "  'this_tel': '8170ffdaba7520b4083a75a6e6795fe1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2000,\n",
       "  'this_tel': '8db2c679c2dea191586c630737dc99c3'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2001,\n",
       "  'this_tel': '951379d33f34d29ee42cdeac6b780cc1'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2002,\n",
       "  'this_tel': '79fa1a88c3d8d6b3dc1265a6046c0441'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2003,\n",
       "  'this_tel': '2cdfdbebb50d21100899361b8e8a4dfd'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2004,\n",
       "  'this_tel': '2093cc6e7c8e9b7f41eb0c8d6bbe0ef6'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2005,\n",
       "  'this_tel': '0127f8fc0208c0794b3a2edbe2a158cc'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2006,\n",
       "  'this_tel': 'a0e586d19c6fe9846c03845530332bf9'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2007,\n",
       "  'this_tel': '345a7aa1097e4332e75abd98c7d4266b'},\n",
       " {'salesstaff_id': 11,\n",
       "  'customer_id': 2008,\n",
       "  'this_tel': 'eb27e71ba048c098e99aaf4b2e4d3939'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2009,\n",
       "  'this_tel': '24c994e21abad0a8b91018e64e84a6e4'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2010,\n",
       "  'this_tel': '3e2b112516b8db3044c09c22d0279681'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2011,\n",
       "  'this_tel': '2b7d6eb47d8b60f4a0be62f7da778a0b'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2012,\n",
       "  'this_tel': 'dfa9b1aca944747c2ebc407484fce670'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2013,\n",
       "  'this_tel': '80a2b01f51603d87c2ba3f6114c703f9'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2014,\n",
       "  'this_tel': '6dda8572c1a36d369981882b2db05ff8'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2015,\n",
       "  'this_tel': '984fcdef13eec26f1977e67b149f58c8'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2016,\n",
       "  'this_tel': 'c8cd655d6170cb1750f1b614858439b2'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2017,\n",
       "  'this_tel': '8b7fb1b554721951a45bc38836530eb3'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2018,\n",
       "  'this_tel': 'b5ebf8a9057c2e5b5ec803d62c5fd75b'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2019,\n",
       "  'this_tel': 'f1ae8dd0675482d7822e9f24dee0e1ef'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2020,\n",
       "  'this_tel': 'b163e2fa72556ce719b4fc024106f9b5'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2021,\n",
       "  'this_tel': 'af8adfcbc8f08d2f891e4736acb2ed99'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2022,\n",
       "  'this_tel': 'e97c65c940cf4e0bd1b8e4f9763e67f8'},\n",
       " {'salesstaff_id': 6,\n",
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       "  'this_tel': '67231e3bae7d077e86589b59395c700d'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2024,\n",
       "  'this_tel': '13067084c8eccdb885d702fdd64439c6'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2025,\n",
       "  'this_tel': 'dadfee8218ed42352a61e6ae47fb1ad9'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2026,\n",
       "  'this_tel': 'e49cf391b965eed0fcba646efcd4130e'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2027,\n",
       "  'this_tel': 'e5fd2d23e0e39aaa9a545cf2549a40ec'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2028,\n",
       "  'this_tel': 'f7bda5fb9459434bea7ef6f1dd2d3ac6'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2029,\n",
       "  'this_tel': '628316968d88351ee446579b1b5067c3'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2030,\n",
       "  'this_tel': 'fbf1bfe3c78192428900f44439f590c0'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2031,\n",
       "  'this_tel': 'e10ad3638e7154ccfb43b928dab1b9e0'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2032,\n",
       "  'this_tel': 'bf2aeb2bc591ca7ebe31bbd9d18217e3'},\n",
       " {'salesstaff_id': 6,\n",
       "  'customer_id': 2033,\n",
       "  'this_tel': '897d8d018756d88248c3ddd6592c86d1'},\n",
       " {'salesstaff_id': 13,\n",
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       "  'this_tel': '005957f6eaddabc5d586496ba4697e94'},\n",
       " {'salesstaff_id': 13,\n",
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       "  'this_tel': '3ca2506c9796174695d53befb1447829'},\n",
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       "  'customer_id': 2822,\n",
       "  'this_tel': 'd000866ec07741c598e0d8cc7b560dfa'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2823,\n",
       "  'this_tel': '24021be75b09774725baf7851805f84c'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2824,\n",
       "  'this_tel': '2839a19710f6a9254c37fb2580cec16b'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2825,\n",
       "  'this_tel': '9b9082097fa396e71e9f603cc2e9f7ef'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2826,\n",
       "  'this_tel': '7b30f04535ae91e7aa98fc7def0c44be'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2827,\n",
       "  'this_tel': '2aee7799e7d0b955cdd6386408d4f623'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2828,\n",
       "  'this_tel': '5afca1f35deea67bf6c90575ebb3a7da'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2829,\n",
       "  'this_tel': 'b0f599c796786f6e5ed562add711d321'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2830,\n",
       "  'this_tel': 'db8cf07b000e94d123f5e55c093c07c3'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2831,\n",
       "  'this_tel': '68a26774e50f90433543f1aee588ed8f'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2832,\n",
       "  'this_tel': '8dc4adcf671b62ec70a26d357a2199f9'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2833,\n",
       "  'this_tel': '3dc7a564710146cd1d2bdcf24c11e8f3'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 2834,\n",
       "  'this_tel': 'd5cebdb1f6da2f20c12049e03d719d2b'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3460,\n",
       "  'this_tel': 'd8a42fb03858efd797dfb1e453fd6fa9'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3461,\n",
       "  'this_tel': '134ff97725c05c417ade0b98f5acb782'},\n",
       " {'salesstaff_id': 9,\n",
       "  'customer_id': 3462,\n",
       "  'this_tel': '82170f04b825000f46f8aca4dad8ccc7'}]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datas1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>salesstaff_id</th>\n",
       "      <th>customer_id</th>\n",
       "      <th>this_tel</th>\n",
       "      <th>custmer_id</th>\n",
       "      <th>tel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>539.0</td>\n",
       "      <td>6f7602c534ce83d367b3c53a4f36c0b7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>540.0</td>\n",
       "      <td>d750c7b30e85efceb15f9838548fc085</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>541.0</td>\n",
       "      <td>4fcd26ac2390e3f54d1a72b87ba4c77c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>542.0</td>\n",
       "      <td>7c134ea8df6ab6e78143eba0a3445e6e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>543.0</td>\n",
       "      <td>0c883e4a18c193c84e9c4785adb4d847</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>9</td>\n",
       "      <td>2834.0</td>\n",
       "      <td>d5cebdb1f6da2f20c12049e03d719d2b</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>9</td>\n",
       "      <td>3460.0</td>\n",
       "      <td>d8a42fb03858efd797dfb1e453fd6fa9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>748</th>\n",
       "      <td>9</td>\n",
       "      <td>3461.0</td>\n",
       "      <td>134ff97725c05c417ade0b98f5acb782</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749</th>\n",
       "      <td>9</td>\n",
       "      <td>3462.0</td>\n",
       "      <td>82170f04b825000f46f8aca4dad8ccc7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>750</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>487.0</td>\n",
       "      <td>a12ddddece31a06b674e41d00c120a35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>751 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     salesstaff_id  customer_id                          this_tel  custmer_id  \\\n",
       "0                2        539.0  6f7602c534ce83d367b3c53a4f36c0b7         NaN   \n",
       "1                2        540.0  d750c7b30e85efceb15f9838548fc085         NaN   \n",
       "2                2        541.0  4fcd26ac2390e3f54d1a72b87ba4c77c         NaN   \n",
       "3                2        542.0  7c134ea8df6ab6e78143eba0a3445e6e         NaN   \n",
       "4                2        543.0  0c883e4a18c193c84e9c4785adb4d847         NaN   \n",
       "..             ...          ...                               ...         ...   \n",
       "746              9       2834.0  d5cebdb1f6da2f20c12049e03d719d2b         NaN   \n",
       "747              9       3460.0  d8a42fb03858efd797dfb1e453fd6fa9         NaN   \n",
       "748              9       3461.0  134ff97725c05c417ade0b98f5acb782         NaN   \n",
       "749              9       3462.0  82170f04b825000f46f8aca4dad8ccc7         NaN   \n",
       "750              5          NaN                               NaN       487.0   \n",
       "\n",
       "                                  tel  \n",
       "0                                 NaN  \n",
       "1                                 NaN  \n",
       "2                                 NaN  \n",
       "3                                 NaN  \n",
       "4                                 NaN  \n",
       "..                                ...  \n",
       "746                               NaN  \n",
       "747                               NaN  \n",
       "748                               NaN  \n",
       "749                               NaN  \n",
       "750  a12ddddece31a06b674e41d00c120a35  \n",
       "\n",
       "[751 rows x 5 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new_mission = pd.DataFrame(df_total)\n",
    "df_new_mission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new_mission.to_sql(\n",
    "\"2020-07-01mission\",\n",
    "conn,\n",
    "index = False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new_mission = df_new_mission.drop(\"tel\",axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new_mission[\"createDate\"] = current_day\n",
    "df_new_mission[\"status_id\"] = 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "OperationalError",
     "evalue": "(pymysql.err.OperationalError) (1054, \"Unknown column 'this_tel' in 'field list'\")\n[SQL: INSERT INTO mission (salesstaff_id, customer_id, this_tel, custmer_id, `createDate`, status_id) VALUES (%(salesstaff_id)s, %(customer_id)s, %(this_tel)s, %(custmer_id)s, %(createDate)s, %(status_id)s)]\n[parameters: ({'salesstaff_id': 2, 'customer_id': 539.0, 'this_tel': '6f7602c534ce83d367b3c53a4f36c0b7', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 540.0, 'this_tel': 'd750c7b30e85efceb15f9838548fc085', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 541.0, 'this_tel': '4fcd26ac2390e3f54d1a72b87ba4c77c', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 542.0, 'this_tel': '7c134ea8df6ab6e78143eba0a3445e6e', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 543.0, 'this_tel': '0c883e4a18c193c84e9c4785adb4d847', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 544.0, 'this_tel': '19de7741b9d2fb317b820984cd7b46dd', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 545.0, 'this_tel': 'ec9817ef0722f3c76138dbc83228dc4c', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 546.0, 'this_tel': '3271d5953121d680d7dbd6dc636d3e5d', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}  ... displaying 10 of 751 total bound parameter sets ...  {'salesstaff_id': 9, 'customer_id': 3462.0, 'this_tel': '82170f04b825000f46f8aca4dad8ccc7', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 5, 'customer_id': None, 'this_tel': None, 'custmer_id': 487.0, 'createDate': '2020-07-01', 'status_id': 7})]\n(Background on this error at: http://sqlalche.me/e/e3q8)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1225\u001b[0m                     self.dialect.do_executemany(\n\u001b[1;32m-> 1226\u001b[1;33m                         \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1227\u001b[0m                     )\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\dialects\\mysql\\mysqldb.py\u001b[0m in \u001b[0;36mdo_executemany\u001b[1;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[0;32m    147\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdo_executemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 148\u001b[1;33m         \u001b[0mrowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecutemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    149\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcontext\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36mexecutemany\u001b[1;34m(self, query, args)\u001b[0m\n\u001b[0;32m    189\u001b[0m                                          \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax_stmt_length\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 190\u001b[1;33m                                          self._get_db().encoding)\n\u001b[0m\u001b[0;32m    191\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36m_do_execute_many\u001b[1;34m(self, prefix, values, postfix, args, max_stmt_length, encoding)\u001b[0m\n\u001b[0;32m    226\u001b[0m             \u001b[0msql\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 227\u001b[1;33m         \u001b[0mrows\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msql\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mpostfix\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    228\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrows\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, query, args)\u001b[0m\n\u001b[0;32m    162\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 163\u001b[1;33m         \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_query\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    164\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_executed\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mquery\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36m_query\u001b[1;34m(self, q)\u001b[0m\n\u001b[0;32m    320\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_clear_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 321\u001b[1;33m         \u001b[0mconn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    322\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_get_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36mquery\u001b[1;34m(self, sql, unbuffered)\u001b[0m\n\u001b[0;32m    504\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_execute_command\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mCOMMAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCOM_QUERY\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msql\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 505\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_affected_rows\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_query_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0munbuffered\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0munbuffered\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    506\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_affected_rows\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36m_read_query_result\u001b[1;34m(self, unbuffered)\u001b[0m\n\u001b[0;32m    723\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mMySQLResult\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 724\u001b[1;33m             \u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    725\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1068\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1069\u001b[1;33m             \u001b[0mfirst_packet\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_packet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1070\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36m_read_packet\u001b[1;34m(self, packet_type)\u001b[0m\n\u001b[0;32m    675\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munbuffered_active\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 676\u001b[1;33m             \u001b[0mpacket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_for_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    677\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mpacket\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\protocol.py\u001b[0m in \u001b[0;36mraise_for_error\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    222\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mDEBUG\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"errno =\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrno\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 223\u001b[1;33m         \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_mysql_exception\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    224\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\err.py\u001b[0m in \u001b[0;36mraise_mysql_exception\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m    106\u001b[0m         \u001b[0merrorclass\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mInternalError\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0merrno\u001b[0m \u001b[1;33m<\u001b[0m \u001b[1;36m1000\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mOperationalError\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 107\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0merrorclass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merrno\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mOperationalError\u001b[0m: (1054, \"Unknown column 'this_tel' in 'field list'\")",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-52-974afa84d5b9>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mconn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0mindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m     \u001b[0mif_exists\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"append\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m )\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(self, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m   2661\u001b[0m             \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2662\u001b[0m             \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2663\u001b[1;33m             \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2664\u001b[0m         )\n\u001b[0;32m   2665\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(frame, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m    519\u001b[0m         \u001b[0mchunksize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    520\u001b[0m         \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 521\u001b[1;33m         \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    522\u001b[0m     )\n\u001b[0;32m    523\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36mto_sql\u001b[1;34m(self, frame, name, if_exists, index, index_label, schema, chunksize, dtype, method)\u001b[0m\n\u001b[0;32m   1315\u001b[0m         )\n\u001b[0;32m   1316\u001b[0m         \u001b[0mtable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1317\u001b[1;33m         \u001b[0mtable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mchunksize\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1318\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misdigit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mislower\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1319\u001b[0m             \u001b[1;31m# check for potentially case sensitivity issues (GH7815)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36minsert\u001b[1;34m(self, chunksize, method)\u001b[0m\n\u001b[0;32m    753\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    754\u001b[0m                 \u001b[0mchunk_iter\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0marr\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mstart_i\u001b[0m\u001b[1;33m:\u001b[0m\u001b[0mend_i\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0marr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata_list\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 755\u001b[1;33m                 \u001b[0mexec_insert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeys\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mchunk_iter\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    756\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    757\u001b[0m     def _query_iterator(\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pandas\\io\\sql.py\u001b[0m in \u001b[0;36m_execute_insert\u001b[1;34m(self, conn, keys, data_iter)\u001b[0m\n\u001b[0;32m    667\u001b[0m         \"\"\"\n\u001b[0;32m    668\u001b[0m         \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrow\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mrow\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata_iter\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 669\u001b[1;33m         \u001b[0mconn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtable\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    670\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    671\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_execute_insert_multi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkeys\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata_iter\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, object_, *multiparams, **params)\u001b[0m\n\u001b[0;32m    980\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobject_\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    981\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 982\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    983\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    984\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_execute_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\sql\\elements.py\u001b[0m in \u001b[0;36m_execute_on_connection\u001b[1;34m(self, connection, multiparams, params)\u001b[0m\n\u001b[0;32m    291\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_execute_on_connection\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    292\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msupports_execution\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 293\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_execute_clauseelement\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    294\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    295\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_clauseelement\u001b[1;34m(self, elem, multiparams, params)\u001b[0m\n\u001b[0;32m   1099\u001b[0m             \u001b[0mdistilled_params\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1100\u001b[0m             \u001b[0mcompiled_sql\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1101\u001b[1;33m             \u001b[0mdistilled_params\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1102\u001b[0m         )\n\u001b[0;32m   1103\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1248\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1249\u001b[0m             self._handle_dbapi_exception(\n\u001b[1;32m-> 1250\u001b[1;33m                 \u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1251\u001b[0m             )\n\u001b[0;32m   1252\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_handle_dbapi_exception\u001b[1;34m(self, e, statement, parameters, cursor, context)\u001b[0m\n\u001b[0;32m   1474\u001b[0m                 \u001b[0mutil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_from_cause\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnewraise\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1475\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[0mshould_wrap\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1476\u001b[1;33m                 \u001b[0mutil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_from_cause\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msqlalchemy_exception\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1477\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1478\u001b[0m                 \u001b[0mutil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\util\\compat.py\u001b[0m in \u001b[0;36mraise_from_cause\u001b[1;34m(exception, exc_info)\u001b[0m\n\u001b[0;32m    396\u001b[0m     \u001b[0mexc_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_value\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_tb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    397\u001b[0m     \u001b[0mcause\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mexception\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 398\u001b[1;33m     \u001b[0mreraise\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexception\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexception\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mexc_tb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcause\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcause\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    399\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    400\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\util\\compat.py\u001b[0m in \u001b[0;36mreraise\u001b[1;34m(tp, value, tb, cause)\u001b[0m\n\u001b[0;32m    150\u001b[0m             \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__cause__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcause\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    151\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 152\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    153\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    154\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1224\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mevt_handled\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1225\u001b[0m                     self.dialect.do_executemany(\n\u001b[1;32m-> 1226\u001b[1;33m                         \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1227\u001b[0m                     )\n\u001b[0;32m   1228\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mparameters\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mno_parameters\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\sqlalchemy\\dialects\\mysql\\mysqldb.py\u001b[0m in \u001b[0;36mdo_executemany\u001b[1;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[0;32m    146\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    147\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdo_executemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 148\u001b[1;33m         \u001b[0mrowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecutemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    149\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcontext\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    150\u001b[0m             \u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_rowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrowcount\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36mexecutemany\u001b[1;34m(self, query, args)\u001b[0m\n\u001b[0;32m    188\u001b[0m             return self._do_execute_many(q_prefix, q_values, q_postfix, args,\n\u001b[0;32m    189\u001b[0m                                          \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax_stmt_length\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 190\u001b[1;33m                                          self._get_db().encoding)\n\u001b[0m\u001b[0;32m    191\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    192\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36m_do_execute_many\u001b[1;34m(self, prefix, values, postfix, args, max_stmt_length, encoding)\u001b[0m\n\u001b[0;32m    225\u001b[0m                 \u001b[0msql\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;34mb','\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    226\u001b[0m             \u001b[0msql\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mv\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 227\u001b[1;33m         \u001b[0mrows\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msql\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mpostfix\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    228\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrowcount\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrows\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    229\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mrows\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, query, args)\u001b[0m\n\u001b[0;32m    161\u001b[0m         \u001b[0mquery\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmogrify\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    162\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 163\u001b[1;33m         \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_query\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    164\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_executed\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mquery\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    165\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\cursors.py\u001b[0m in \u001b[0;36m_query\u001b[1;34m(self, q)\u001b[0m\n\u001b[0;32m    319\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_last_executed\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mq\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    320\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_clear_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 321\u001b[1;33m         \u001b[0mconn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    322\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_get_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    323\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrowcount\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36mquery\u001b[1;34m(self, sql, unbuffered)\u001b[0m\n\u001b[0;32m    503\u001b[0m                 \u001b[0msql\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msql\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mencoding\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'surrogateescape'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    504\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_execute_command\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mCOMMAND\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCOM_QUERY\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msql\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 505\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_affected_rows\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_query_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0munbuffered\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0munbuffered\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    506\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_affected_rows\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    507\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36m_read_query_result\u001b[1;34m(self, unbuffered)\u001b[0m\n\u001b[0;32m    722\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    723\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mMySQLResult\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 724\u001b[1;33m             \u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    725\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    726\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mserver_status\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1067\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1068\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1069\u001b[1;33m             \u001b[0mfirst_packet\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_packet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1070\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1071\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mfirst_packet\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_ok_packet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\connections.py\u001b[0m in \u001b[0;36m_read_packet\u001b[1;34m(self, packet_type)\u001b[0m\n\u001b[0;32m    674\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munbuffered_active\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    675\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munbuffered_active\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 676\u001b[1;33m             \u001b[0mpacket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_for_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    677\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mpacket\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    678\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\protocol.py\u001b[0m in \u001b[0;36mraise_for_error\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    221\u001b[0m         \u001b[0merrno\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_uint16\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    222\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mDEBUG\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"errno =\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrno\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 223\u001b[1;33m         \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_mysql_exception\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    224\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    225\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdump\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\anaconda\\lib\\site-packages\\pymysql\\err.py\u001b[0m in \u001b[0;36mraise_mysql_exception\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m    105\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0merrorclass\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    106\u001b[0m         \u001b[0merrorclass\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mInternalError\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0merrno\u001b[0m \u001b[1;33m<\u001b[0m \u001b[1;36m1000\u001b[0m \u001b[1;32melse\u001b[0m \u001b[0mOperationalError\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 107\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0merrorclass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merrno\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mOperationalError\u001b[0m: (pymysql.err.OperationalError) (1054, \"Unknown column 'this_tel' in 'field list'\")\n[SQL: INSERT INTO mission (salesstaff_id, customer_id, this_tel, custmer_id, `createDate`, status_id) VALUES (%(salesstaff_id)s, %(customer_id)s, %(this_tel)s, %(custmer_id)s, %(createDate)s, %(status_id)s)]\n[parameters: ({'salesstaff_id': 2, 'customer_id': 539.0, 'this_tel': '6f7602c534ce83d367b3c53a4f36c0b7', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 540.0, 'this_tel': 'd750c7b30e85efceb15f9838548fc085', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 541.0, 'this_tel': '4fcd26ac2390e3f54d1a72b87ba4c77c', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 542.0, 'this_tel': '7c134ea8df6ab6e78143eba0a3445e6e', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 543.0, 'this_tel': '0c883e4a18c193c84e9c4785adb4d847', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 544.0, 'this_tel': '19de7741b9d2fb317b820984cd7b46dd', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 545.0, 'this_tel': 'ec9817ef0722f3c76138dbc83228dc4c', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 2, 'customer_id': 546.0, 'this_tel': '3271d5953121d680d7dbd6dc636d3e5d', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}  ... displaying 10 of 751 total bound parameter sets ...  {'salesstaff_id': 9, 'customer_id': 3462.0, 'this_tel': '82170f04b825000f46f8aca4dad8ccc7', 'custmer_id': None, 'createDate': '2020-07-01', 'status_id': 7}, {'salesstaff_id': 5, 'customer_id': None, 'this_tel': None, 'custmer_id': 487.0, 'createDate': '2020-07-01', 'status_id': 7})]\n(Background on this error at: http://sqlalche.me/e/e3q8)"
     ]
    }
   ],
   "source": [
    "df_new_mission.to_sql(\n",
    "\"mission\",\n",
    "    conn,\n",
    "    index=False,\n",
    "    if_exists = \"append\"\n",
    "\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['salesstaff_id', 'customer_id', 'this_tel', 'custmer_id', 'createDate',\n",
       "       'status_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new_mission.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new_mission.columns = ['salesstaff_id', 'customer_id', 'this_tel', 'custmer_id', 'createDate',\n",
    "       'status_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df_new_mission' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-be60a8bd7eb1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m df_new_mission.to_sql(\n\u001b[0m\u001b[0;32m      2\u001b[0m     \u001b[1;34m\"mission\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mconn\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0mindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m     \u001b[0mif_exists\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"append\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'df_new_mission' is not defined"
     ]
    }
   ],
   "source": [
    "df_new_mission.to_sql(\n",
    "    \"mission\",\n",
    "    conn,\n",
    "    index=False,\n",
    "    if_exists = \"append\"\n",
    "\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "200/4000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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